Time and Date: 10:00 - 12:30 on 20th Sep 2016

Room: H - Ontvangkamer

Chair: Marion Dumas

22000

Session 1?: Modeling Law and Social Cohesion

22001

Cooperation on the tipping point?: how do rules,norms and law violations undermine society??
[abstract]

Abstract: In evolutionary game theory, success-driven migration has been found to be important for the emergence of cooperation, in particular when cooperative communities can be established. However, in real-life, migrations are often associated with illegal activities or other behavior deviating from the local social norms. If widespread, these activities may jeopardize cooperation and destabilize societies. We resort to a simple spatial game with individuals endowed with deterministic prisoner's dilemma and success-driven migration rules, as well as an additional stochastic property violation migration rule. These rules altogether reflect the odds of a fully rational individual engaging in illegal activity, against the enforcement of individual, social and institutional rules. We find that little rule violation helps cement cooperative communities, capable of handling violations locally. However, with increasingly prevalent rule-violating activity, cooperators aggregate and form larger clusters against defectors. These massive clusters of cooperators turn out to be fragile against invasion by defectors, and they ultimately collapse. Our results compare to climate change and other tipping point phenomena: Rule-violating behaviors may create the conditions of local weaknesses early on, which trigger hardly reversible systemic consequences for society on the long run. This has implications for policies on immigration, labor mobility, public discourse, and innovation.

Abstract: Complexity cannot be strictly defined, only situated in between order and disorder. A complex system is presented as a collection of interacting agents, representing components as diverse as people, cells or organizations. Because of the non-linearity of the interactions, the overall system evolution is to a substantial degree unpredictable and uncontrollable. One of the research topics in the Multi-Agent Systems area is using models that represent social structures, such as a network of organizations that create alliances, to analyze more objectively the emergent behavior of such a regulated open system. In our research, we study the impact of rules that describe the expected behavior of actors in such system. For this, we model both the rules as well as some aspects of the behavior of the agents that are subjected to these rules. In our simulations, we model complex networks that consist of many different actors that may represent individuals or organizations, which are related to each other by various types of relationships. Examples may be dependencies on goals, conflicts over resources and various beliefs. Legal rules bind the actors and because they are part of an organizational network (in this research a distributed network) they are bounded by a set of norms, including legal norms, contracts, and agreements. Obviously, actors may comply with the rules or not and being able to notice non-compliance and responding to it adequately is one of the reasons why we are interested in this research topic. The inherent complexity and unpredictability of this social society demand new kinds of coordination mechanism that focus on rapid joint responses and collective actions instead of centralized predictive planning. We present a multi-agent framework intended to explore the emergent behavior of a regulated complex system. Our approach is the result of ongoing investigations after the impact of regulations on social regimes, with the purpose of understanding social complexity as an emergent phenomenon floating on the characteristics of the models of the involved agents. In order to reduce the potentially infinite variance of individuals that are interacting in our real societies, we propose to apply canonical agents as an abstract model of agents. This will allow us to model the domain system with sufficient accuracy while being able to reduce the computational demands of our simulation. Our framework relies on agent-role modeling and simulation as a tool for examination the speci?c manifestations of emergent behavior. It proceeds along three steps. First, we explore how an institutional perspective can handle in our computational framework. Roles, institutions, and rules become components of the agent architecture. Second, we extend the agent architecture to address the problem of choosing an appropriate plan in an uncertain situation when an agent has to respond to and act upon uncertain, and incomplete information. Third, the resulting scenario representation is synthesized as agent programs. These scripts correspond to descriptions of agent roles observed in a social setting.

Abstract: Over the past decades, the study of networks has brought remarkable advances in our understanding of complex systems. As various scholars have pointed out, law, too, can be viewed as a complex system. It follows, then, that we should use tools from network science to analyze law, legal rules, and legal systems. While the number of publications exploring networks in law has surged in recent years, most authors draw on the same small set of research questions and network definitions. My paper aims to change that. I describe law as a network of networks and develop a taxonomy of its elements, distinguishing nodes by category and edges by structure, order, and type of the underlying relations. This taxonomy illustrates that to fully understand law?s structure and dynamics, we need to embrace its complexity in our network definitions and investigate the interplay between the different kinds of networks in law. Therefore, the paper concludes with some thoughts on how my taxonomy could pave the way towards a truly interdisciplinary research agenda for the science of legal networks.

Corinna Coupette

22006

Unravelling the complexity of legal decisions with network science
[abstract]

Abstract: Do case citations reflect the ?real? importance of individual judgments for the legal system concerned? This question has long been puzzling empirical legal scholars. Existing research typically studies case citation networks as a whole applying traditional network metrics stemming from graph theory. Those approaches are able to detect globally important cases, but since they do not take time explicitly into account, they cannot provide a comprehensive picture of the dynamics behind the network structure and its evolution.This talk intends to provide such a description by presenting the results obtained in a series of empirical and interdisciplinary studies conducted on two different jurisdictions. In the first series of studies, we analyze the corpus of decisions made by the International Criminal Court (ICC) since its creation. This work show how network metrics can help revealing some fundamental aspects of the cases such as the role and the rights of the victims in the trials and the particular emphasis that the Court placed on the notion of reparations.In a second series of studies, we use two node importance metrics that take time into account to study important cases of Court of Justice of the European Union over time. We then compare cases deemed as important by the metrics, with a set of 50 cases selected by the Court as the most important (landmark) cases. Our contribution here is twofold. First, with regard to network science, we show that structural and time-related properties are complementary, and necessary to obtain a complete and nuanced picture of the citation network. Second, with regard to the case law of the Court, these studies provide empirical evidence clarifying the motivation of the Court when selecting the landmark cases, revealing the importance of symbolic and historical cases in the selection. In addition, the temporal analysis sheds new light on the network properties specific to the landmark cases that distinguishes them from the rest of the cases. We validate our results by providing legal interpretations that sustain the highlights provided by the proposed network analysis.

Abstract: All legal systems rely on case law to ensure their functioning. Most empirical legal studies to date have used classical statistical techniques to characterize the case law of a single court. Thus, our quantitative knowledge about case law as a whole is still very limited. Here, we propose the concept of case law fitness to systematically investigate the workings of case law from a network theoretic perspective. In particular, we study the relationships between decisions and bodies of case law from multiple sources. We develop hypotheses regarding the material, institutional, temporal, spatiocultural, and personal factors that may influence how cases cite and get cited. To test our hypotheses, we present empirical results and insights into some of the determinants of case law fitness. Using a dataset containing not only U.S. Supreme Court cases but also decisions from U.S. Courts of Appeals and U.S. District Courts, we study the temporal evolution of the entire citation network as well as the age structure of links. We further analyze the relationship between intra- and inter-institutional citations and the relevance of institutional hierarchies between courts. Finally, we examine the geospatial distribution of inter-institutional citations. The results point towards open questions regarding the role of cases in the evolution of legal systems and draw attention to some of the methodological challenges lying ahead.